Jun 22, 2021
What role does real-time and historical data play in quality control?
When it comes to data, there is one thing constant about it, “It Changes Every Single Second.”
From business emails to growth statistics, the information which was useful a day ago turns to be outdated, and your inability to align with data in real-time leads to massive effects on your decision-making.
Nevertheless, it is significantly essential for testing and QA services providers to understand the importance of data quality in quality control.
As per the reports, Poor data quality could cost $ 9.7 million to an organization annually, and the year 2016 accounted for a loss of $ 13 trillion per year only in the United States. Furthermore, no or reduced access to real-time data leads to a 20 percent decrease in worker productivity while failing 40 percent of business initiatives in achieving defined objectives.
Enable Predictable Software Outcomes For Better ROI
To be concise, having no access to real-time data could lead to missed opportunities occurring from reputation loss and misdirect resources. Also, having access to fact-based information than mere intuition-based work is necessary for driving efficiency. Therefore, all the QA initiatives must be led considering the five important benchmarks of real-time and historical data in mind. These include:
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Completeness: To ensure zero gaps between data collected and data supposed to be collected.
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Consistency: To ensure data collected aligns with what needs to be collected for quality.
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Accuracy: To ensure data collected is relevant, sufficient, and precise.
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Validity: To ensure data used in the quality assurance process must be inspired from the process and not final outcomes.
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Timeliness: To ensure data is collected on time and is put to use efficiently in a timely manner.
With ever-escalating user expectations on the product development, meeting the Quality Assurance goals with websites and application testing has pushed organizations towards mechanisms that can help work on enhanced standardization. Historical data and real-time industry insights have therefore turned to be a prominent part of the testing strategy when goals are improving software outcomes.
Since the ultimate goal behind hiring Quality Assurance Services in India is improving the product functionality, referring to data extracted from past failure analysis helps sustain the quality feedback loop and meet the productivity goals. Moreover, historical data, when coupled with real-time insights, makes it easier to predict when a failure could occur. Such chronology in the process then leads to reduced chances of trouble.
Let us quickly jump on the benefits that real-time data and historical data could offer in the process of quality control:
Fault Reduction
Using historical and real-time data during the development and testing process enables QA teams to locate defects in advance. The advantage to pinpoint when and where a defect could appear helps rapid releases of product to the market while offering functionality and scalability benefits. In simple words, the purpose of using historical data and tracking real-time data is to locate defect patterns and to improve the code quality for all test cases leading to success.
Also, the use of historical fault detection data can predict instances of failure for the current version of the modern applications allowing the use of analytical information to proactively address those common instances of failure. This can even add benefit to companies that need help identifying breakdown for performance testing for every new functionality or service added to the system or for any changes made to the source code.
All in all, historical data helps teams to detect any type of external and internal issues that might affect the application performance by enabling users to identify the cause of the problem, work on them, and create a product with greater impact by rearranging the schedule for release.
Test Execution History
If you need to glean some valuable data that can help streamline the continuous integration process, make sure you never forget to consider historical data into the development and QA process. This is because the absence of coverage data from the past makes it more difficult for the user to work on test validation, thus extending the time to market.
On the other hand, the use of historical data provides all the required information related to a test from past incidents simplifying the process for the current release. Though the history data cannot be accommodated for the newly written test codes, the metrics from past failure data can still help save time for the code execution for the functionalities achieved through similar codes.
Moreover, organizations that rely on historical test data could work on similar execution test cases, and the information generated through these cases can further be used to lead future projects. In technical terms, the process is called the sequence of method calls, where a set of statements is used to invoke another statement.
Putting The Information To Use
At present, there is the large number of organizations that have started to leverage the power of big data into the development process. This is because big data can design software development and testing process for added productivity within the pre-defined development environment.
This is the only point where the best software testing company makes a difference in comparison to a standard development company that resists investing in data and ultimately faces the loss of longevity with the final products.
At BugRaptors, we have a team of leading ISTQB certified experts who bring you the best of testing and QA solutions that are made to leverage data from one ecosystem to the other while overcoming past, existing, and predicted mistakes with the process.
